A curated, verified, cross-vendor directory of AI agent harnesses — the runtime scaffolding that turns a model into an agent.
◆ 74 harnesses profiled · 9-axis capability schema · last verified 2026-07-08
The most-starred open-source coding agent of 2026 (~183k stars, MIT, TypeScript): a polished terminal TUI with 75+ providers, LSP feedback, Tab-switchable build/plan agents plus background subagents, SKILL.md support, and optional paid model access via OpenCode Go ($10/mo) and pay-as-you-go Zen gateway.
OpenAI's open-source (Apache-2.0) Rust-rewritten terminal coding agent, distinguished by kernel-level OS sandboxing (Apple Seatbelt on macOS, Landlock/seccomp on Linux), a 272K-1M token context with GPT-5.x Codex models, MCP support, and cloud handoff to Codex web tasks.
Alibaba's Apache-2.0 terminal agent (originally a Gemini CLI fork) optimized for Qwen3-Coder models, distinguished by broad provider flexibility (OpenAI/Anthropic/Gemini/Qwen APIs plus Ollama/vLLM local models), skills/subagents primitives, headless mode, and TypeScript/Python/Java SDKs.
Kilo's open-source terminal agent (Kilo CLI 1.0, built on the MIT-licensed OpenCode foundation) distinguished by support for 500+ models with zero-markup BYOK pricing, an MCP marketplace, and cross-surface continuity where a task can move between Slack, VS Code/JetBrains, cloud, and terminal.
A batteries-included 2026 fork of Pi (created Dec 31, 2025; ~17k stars) that inverts Pi's minimalism: hash-anchored edits that reject stale patches, LSP and DAP debugger integration, in-process ripgrep/bash, 40+ providers, 32 tools, and subagent orchestration.
Mistral's minimal Apache-2.0 CLI coding agent (launched December 2025 alongside the open-weight Devstral 2 models, which score a vendor-reported 72.2% on SWE-bench Verified), distinguished by a deliberately lean self-hostable design — file read/write/patch, stateful shell, grep, and todo tools — with fully open, locally runnable model weights.
Moonshot AI's MIT-licensed TypeScript terminal agent (launched June 2026, replacing its earlier CLI) built around the token-efficient Kimi K2.7-Code 1T-parameter MoE model with 256K context, distinguished by built-in coder/explore/plan subagents running in isolated contexts and configurable OpenAI-compatible providers including local deployments.